Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: receiving, by an Enterprise Service Bus (ESB) component of an ESB system, from a first system, a database query formatted in a first format; generating a Structured Query Language (SQL) query plan for executing the database query, wherein the SQL query plan comprises a plurality of operations; generating an execution sequence based on the SQL query plan, by mapping each of the plurality of operations within the SQL query plan to be processed by either the ESB component a second system, wherein mapping the plurality of operations comprises: upon determining that a first operation of the plurality of operations is a database operation used to insert data into a database, generating an HTTP request to carry out the first operation, wherein the HTTP request is a POST request; mapping, to the second system, the first operation comprising the HTTP request; and mapping, to the ESB component, a second operation comprising a data processing operation to be performed on a result of the database operation; transmitting, based on the mapping, the HTTP request to a RESTful API provided by the second system, wherein the second system is configured to execute the HTTP request against the database; receiving, by the ESB component, from the second system, a first set of results generated by executing the HTTP request against the database; generating, by the ESB component, a set of query results for the database query by processing the received first set of results, comprising executing, based on the mapping, the data processing operation on the first set of results received from the second system; and sending, to the first system, the set of query results.
This invention relates to an Enterprise Service Bus (ESB) system that processes database queries by distributing operations between the ESB component and a second system. The problem addressed is the efficient execution of database queries, particularly when operations involve both database interactions and data processing. The system receives a database query in a first format from a first system and generates a Structured Query Language (SQL) query plan with multiple operations. The ESB component then maps these operations to either itself or a second system. If an operation is a database operation (e.g., inserting data), the ESB generates an HTTP POST request and maps it to the second system, which executes the request against the database via a RESTful API. The ESB processes the results from the second system, performing any required data processing operations, and sends the final query results back to the first system. This approach optimizes query execution by leveraging the strengths of both the ESB and the second system, improving efficiency and scalability.
2. The method of claim 1 , wherein the first set of results comprises one or more JSON objects, and wherein generating the set of query results for the database query comprises mapping the one or more JSON objects to one or more SQL formatted set of query results.
This invention relates to data processing systems that handle JSON (JavaScript Object Notation) data and SQL (Structured Query Language) databases. The problem addressed is the difficulty of efficiently querying and retrieving JSON-formatted data from a database system that primarily uses SQL for data storage and retrieval. JSON is a lightweight, human-readable data interchange format commonly used in web applications, while SQL is a standardized language for managing relational databases. The mismatch between these formats can create inefficiencies in data processing workflows, particularly when JSON data needs to be queried or transformed into a structured format compatible with SQL-based systems. The invention describes a method for generating query results from a database query where the initial results are in JSON format. The method involves mapping the JSON objects to SQL-formatted query results. This mapping process ensures that the JSON data is converted into a structured format that can be seamlessly integrated with SQL-based database operations. The method may include parsing the JSON objects, extracting relevant data fields, and restructuring them into a tabular format compatible with SQL queries. This approach allows for efficient data retrieval and manipulation, bridging the gap between JSON and SQL data formats. The invention is particularly useful in systems where JSON data is stored or processed alongside traditional relational database structures, enabling smoother integration and interoperability between different data formats.
3. The method of claim 1 , wherein the data processing operation comprises one of (i) a join and (ii) a sort.
This invention relates to data processing systems, specifically methods for optimizing data operations in distributed computing environments. The problem addressed is the inefficiency in executing complex data operations, such as joins and sorts, across multiple nodes in a distributed system, leading to high latency and resource consumption. The method involves analyzing a data processing operation to determine its computational requirements and then dynamically allocating resources across a distributed system to optimize performance. For a join operation, the method partitions input datasets based on key values and distributes the partitions across nodes to minimize data transfer and maximize parallel processing. For a sort operation, the method employs a distributed sorting algorithm that divides the dataset into segments, sorts each segment locally, and then merges the results efficiently across nodes. The system monitors the progress of the operation and adjusts resource allocation in real-time to handle bottlenecks, such as uneven data distribution or node failures. This adaptive approach ensures that the operation completes efficiently while minimizing overhead. The method is particularly useful in large-scale data processing frameworks, such as distributed databases or big data analytics platforms, where performance and scalability are critical.
4. The method of claim 1 , wherein the database query is received from a database driver that intercepts SQL queries on the first system and reroutes them, and wherein the set of query results comprises one or more JSON objects.
A system and method for processing database queries involves intercepting SQL queries on a first system, rerouting them to a second system, and returning query results in a structured format. The method includes receiving a database query from a database driver that intercepts SQL queries on the first system and reroutes them to the second system. The second system processes the query and generates a set of query results, which are then transmitted back to the first system. The query results are formatted as one or more JSON objects, allowing for structured data exchange. The database driver acts as an intermediary, capturing SQL queries before they reach the original database, modifying or rerouting them as needed, and ensuring the results are returned in a standardized JSON format. This approach enables seamless integration between different database systems, improves query flexibility, and supports modern applications that rely on JSON-based data structures. The system enhances interoperability and simplifies data processing by converting traditional SQL queries into a more accessible and widely compatible format.
5. The method of claim 1 , wherein generating the execution sequence further comprises assigning a respective in queue and a respective out queue for each of the first data processing operation and the HTTP request, and defining data transmission paths between the plurality of in queues and out queues.
This invention relates to data processing systems that handle both internal data operations and external HTTP requests. The problem addressed is efficiently managing and executing a sequence of operations where some tasks involve internal data processing while others require external HTTP communications, ensuring proper data flow and coordination between these different types of tasks. The method involves generating an execution sequence for a plurality of data processing operations, including at least one internal data processing operation and at least one HTTP request. Each operation is assigned a respective in queue and a respective out queue, which act as buffers for input and output data. Data transmission paths are defined between the in queues and out queues of the operations, establishing the flow of data between them. This ensures that data produced by one operation is correctly routed to the next operation in the sequence, whether it is another internal data processing step or an HTTP request. The system dynamically manages these queues and paths to optimize performance and avoid bottlenecks, particularly when handling mixed workloads of internal and external tasks. The approach improves efficiency by reducing latency and ensuring proper synchronization between different types of operations.
6. The method of claim 1 , the method further comprising converting the database query from a first database schema associated with a legacy database to a second database schema associated with the database of the second system, wherein the first and second database schemas are different.
This invention relates to data migration and integration systems, specifically addressing the challenge of querying data across systems with incompatible database schemas. The method enables seamless data access by converting database queries between different schema formats, allowing legacy systems to interact with modern databases without requiring schema modifications. The process involves receiving a database query from a first system, where the query is formatted according to a legacy database schema. The query is then translated into a second schema format compatible with a target database system, enabling the query to be executed against the second system's database. This conversion ensures that the query structure, syntax, and data references are accurately mapped between the two schemas, preserving the original query's intent while adapting it to the target system's requirements. The method supports bidirectional data access, allowing queries from either system to be processed by the other, facilitating integration between heterogeneous database environments. This approach eliminates the need for manual schema adjustments or intermediate data transformation steps, streamlining data retrieval and reducing compatibility issues in multi-system architectures.
7. A system, comprising: a first system; a second system; and an enterprise service bus (ESB) system comprising one or more computer processors and configured perform an operation by operation of the one or more computer processors, the operation comprising: receiving, by an ESB component of the ESB system, from the first system, a database query formatted in a first format; generating a Structured Query Language (SQL) query plan for executing the database query, wherein the SQL query plan comprises a plurality of operations; generating an execution sequence based on the SQL query plan, by mapping each of the plurality of operations within the SQL query plan to be processed by either the ESB component or a second system, wherein mapping the plurality of operations comprises: upon determining that a first operation of the plurality of operations is a database operation used to insert data into a database, generating an HTTP request to carry out the first operation, wherein the HTTP request is a POST request; mapping, to the second system, the first operation comprising the HTTP request; and mapping, to the ESB component, a second operation comprising a data processing operation to be performed on a result of the database operation; transmitting, based on the mapping, the HTTP request to a RESTful API provided by the second system, wherein the second system is configured to execute the HTTP request against the database; receiving, by the ESB system, from the second system, a first set of results generated by executing the HTTP request against the database; generating, by the ESB system, a set of query results for the database query by processing the received first set of results, comprising executing, based on the mapping, the data processing operation on the first set of results received from the second system; and sending, to the first system, the set of query results.
The system involves an enterprise service bus (ESB) that facilitates communication between two systems and a database. The ESB receives a database query from the first system in a specific format and converts it into a SQL query plan. This plan is broken down into multiple operations, some of which are executed by the ESB itself, while others are delegated to the second system. For database operations like inserting data, the ESB generates an HTTP POST request and sends it to a RESTful API provided by the second system. The second system executes the request against the database and returns the results to the ESB. The ESB then processes these results, performing any necessary data processing operations, and sends the final query results back to the first system. This approach allows the ESB to act as an intermediary, distributing tasks between itself and the second system to efficiently handle database queries and processing. The system ensures seamless integration between different systems and databases while maintaining flexibility in how operations are executed.
8. The system of claim 7 , wherein the first set of results comprises one or more JSON objects, and wherein generating the set of query results for the database query comprises mapping the one or more JSON objects to one or more SQL formatted set of query results.
This invention relates to data processing systems that handle JSON (JavaScript Object Notation) data and convert it into SQL (Structured Query Language) formatted results for database queries. The problem addressed is the incompatibility between JSON data structures and traditional SQL-based database systems, which often require JSON data to be transformed into a relational format for efficient querying and processing. The system includes a data processing module that receives a database query and retrieves a first set of results in JSON format from a data source. The system then processes these JSON objects by mapping them into SQL-formatted query results. This conversion ensures that the JSON data can be seamlessly integrated into SQL-based database operations, allowing for consistent and efficient data handling. The mapping process involves translating JSON key-value pairs into SQL-compatible structures, such as tables or rows, while preserving the hierarchical relationships within the original JSON data. The system may also include additional components for optimizing the query performance, such as caching mechanisms or indexing strategies, to enhance the speed and accuracy of the JSON-to-SQL conversion. By automating this transformation, the system enables developers to work with JSON data in environments that primarily rely on SQL databases, reducing the need for manual data conversion and improving overall system efficiency.
9. The system of claim 7 , wherein the data processing operation comprises a sort.
A data processing system is designed to optimize the execution of data operations, particularly focusing on sorting tasks. The system includes a processing unit configured to perform data processing operations, such as sorting, on input data. The processing unit is further configured to determine whether a data processing operation is a sort operation and, if so, to apply a specialized sorting algorithm or optimization technique to improve efficiency. The system may also include a memory unit to store the input data and intermediate results, as well as an interface to receive the input data and output the processed results. The sorting operation may involve comparing data elements, rearranging them in a specified order, and handling large datasets efficiently. The system may further include mechanisms to detect patterns or redundancies in the data to enhance sorting performance. The overall goal is to reduce computational overhead and improve the speed and accuracy of sorting operations in data processing tasks.
10. The system of claim 7 , wherein the database query is received from a database driver that intercepts SQL queries on the first system and reroutes them, and wherein the set of query results comprises one or more JSON objects.
A system for database query processing enhances data retrieval efficiency by intercepting and rerouting SQL queries. The system operates within a computing environment where a database driver captures SQL queries generated by applications on a first system. Instead of directly executing these queries on a local database, the driver reroutes them to a centralized query processing system. This system processes the queries and returns results in the form of one or more JSON objects, which are then delivered back to the originating application. The use of JSON objects allows for flexible and structured data representation, facilitating integration with modern applications that rely on web-based or API-driven architectures. By centralizing query processing, the system reduces redundant computations, optimizes resource utilization, and ensures consistent data handling across multiple applications. The approach is particularly useful in distributed systems where multiple applications require access to the same database, as it minimizes the need for each application to maintain its own query logic and connection management. The system also supports scalability by offloading query processing to a dedicated backend, allowing the first system to focus on application logic rather than database interactions.
11. The system of claim 7 , wherein generating the execution sequence further comprises assigning a respective in queue and a respective out queue for each of the first data processing operation and the HTTP request, and defining data transmission paths between the plurality of in queues and out queues.
This invention relates to a data processing system that optimizes the execution of operations, including HTTP requests, by dynamically managing data flow between processing stages. The system addresses inefficiencies in traditional data processing pipelines where operations are executed sequentially or without proper coordination, leading to bottlenecks, delays, or resource underutilization. The system includes a plurality of data processing operations and HTTP requests that are executed in a defined sequence. Each operation and HTTP request is assigned a dedicated in queue and out queue, which act as buffers for input and output data, respectively. The system further defines data transmission paths between these queues, ensuring that data flows efficiently from one operation to the next without unnecessary delays or conflicts. This queue-based approach allows for parallel processing where possible, reducing overall execution time. The system dynamically adjusts the execution sequence based on dependencies between operations, ensuring that data is available when needed. For example, if an HTTP request depends on the output of a prior data processing operation, the system ensures the request is only executed after the required data is available in the corresponding out queue. This prevents deadlocks and ensures smooth data flow throughout the pipeline. By managing queues and transmission paths, the system improves resource utilization, reduces latency, and enhances scalability in data processing workflows. The invention is particularly useful in environments where multiple operations and HTTP requests must be coordinated efficiently, such as web servers, cloud computing, or distributed systems.
12. The system of claim 7 , the operation further comprising converting the database query from a first database schema associated with a legacy database to a second database schema associated with the database of the second system, wherein the first and second database schemas are different.
This invention relates to a system for migrating data between systems with different database schemas. The problem addressed is the difficulty of transferring data from a legacy database to a modern system when the two systems use incompatible database structures. The system includes a data migration module that extracts data from a legacy database and converts it into a format compatible with a target system. The conversion process involves transforming the database query from the legacy schema to the target schema, ensuring that the data remains accurate and usable in the new system. The system also includes a data validation module to verify the integrity and consistency of the migrated data. The migration process is automated, reducing manual effort and minimizing errors during the transition. This solution is particularly useful for organizations upgrading their database infrastructure while maintaining data accessibility and reliability. The system ensures seamless integration between legacy and modern systems, allowing for uninterrupted business operations during the migration process.
13. A computer program product for providing access to a remote database, the computer program product comprising: a computer-readable storage medium containing computer-readable program code that, when executed by operation of one or more computer processors, performs an operation, comprising: receiving, by an Enterprise Service Bus (ESB) component of an ESB system, from a first system, a database query formatted in a first format; generating a Structured Query Language (SQL) query plan for executing the database query, wherein the SQL query plan comprises a plurality of operations; generating an execution sequence based on the SQL query plan, by mapping each of the plurality of operations within the SQL query plan to be processed either the ESB component or a second system, wherein mapping the plurality of operations comprises: upon determining that a first operation of the plurality of operations is a database operation used to insert data into a database, generating an HTTP request to carry out the first operation, wherein the HTTP request is a POST request; mapping, to the second system, the first operation comprising the HTTP request; and mapping, to the ESB component, a second operation comprising a data processing operation to be performed on a result of the database operation; transmitting, based on the mapping, the HTTP request to a RESTful API provided by the second system, wherein the second system is configured to execute the HTTP request against the database; receiving, by the ESB component, from the second system, a first set of results generated by executing the HTTP request against the database; generating, by the ESB component, a set of query results for the database query by processing the received first set of results, comprising executing, based on the mapping, the data processing operation on the first set of results received from the second system; and sending, to the first system, the set of query results.
This invention relates to a system for accessing a remote database using an Enterprise Service Bus (ESB) to manage and execute database queries. The system addresses the challenge of efficiently processing database operations across distributed systems by leveraging an ESB to coordinate query execution and data processing. The system receives a database query from a first system, formatted in a specific format, and processes it through an ESB component. The ESB generates a Structured Query Language (SQL) query plan, which includes multiple operations. These operations are then mapped to either the ESB component or a second system for execution. For database operations like inserting data, the ESB generates an HTTP POST request and maps this operation to the second system, which executes the request against the database via a RESTful API. The ESB retains control of data processing operations, such as transforming query results, and performs these tasks locally. After the second system executes the database operation, it returns the results to the ESB. The ESB processes these results by applying the mapped data processing operations and generates a final set of query results. These results are then sent back to the first system. This approach optimizes query execution by distributing workloads between the ESB and the second system, improving efficiency and scalability in distributed database access scenarios.
14. The computer program product of claim 13 , wherein the database query is received from a database driver that intercepts SQL queries on the first system and reroutes them, and wherein the set of query results comprises one or more JSON objects.
This invention relates to database query processing in distributed systems, specifically addressing the challenge of efficiently handling and transforming database queries between different systems. The system includes a database driver that intercepts SQL queries on a first system, reroutes them to a second system, and processes the query results. The database driver modifies the intercepted SQL queries before forwarding them to the second system, ensuring compatibility and optimal performance. The query results, which may include one or more JSON objects, are then returned to the first system. This approach enables seamless integration between systems with different database structures or protocols, improving interoperability and reducing the need for manual query adjustments. The system may also include additional components for query optimization, such as analyzing query patterns or caching frequently accessed data, to enhance performance. The invention is particularly useful in environments where multiple systems with varying database architectures need to interact, such as in cloud computing or enterprise applications.
15. The computer program product of claim 13 , wherein generating the execution sequence further comprises assigning a respective in queue and a respective out queue for each of the first data processing operation and the first HTTP request, and defining data transmission paths between the plurality of in queues and out queues.
This invention relates to optimizing data processing workflows in distributed systems, particularly for handling HTTP requests and data operations. The problem addressed is the inefficiency in managing data flow between different processing stages, leading to bottlenecks and delays in execution. The solution involves a computer program product that generates an execution sequence for processing data. This sequence includes assigning separate input and output queues for each data processing operation and HTTP request. The system defines data transmission paths between these queues to ensure efficient data routing. The execution sequence is generated based on predefined rules, such as dependencies between operations or priority levels, to optimize the workflow. The invention also includes mechanisms to dynamically adjust the execution sequence in response to changes in system conditions, such as network latency or resource availability. This ensures that the workflow remains efficient even under varying operational conditions. The use of dedicated queues and defined paths reduces contention for shared resources and minimizes delays in data transmission. The system may also include monitoring capabilities to track the performance of the execution sequence and identify potential improvements. This feedback loop allows for continuous optimization of the workflow. The overall approach enhances the efficiency and reliability of data processing in distributed environments.
16. The computer program product of claim 13 , the operation further comprising converting the database query from a first database schema associated with a legacy database to a second database schema associated with the database of the second system, wherein the first and second database schemas are different.
This invention relates to database query conversion in systems integrating legacy databases with modern database systems. The problem addressed is the incompatibility between different database schemas, which prevents seamless data exchange and query execution across systems. The solution involves a computer program product that facilitates query conversion between a legacy database and a modern database system. The program converts a database query from a first schema associated with the legacy database to a second schema associated with the modern database, where the two schemas are structurally different. This conversion ensures that queries formulated for the legacy system can be executed in the modern system without manual reconfiguration or schema mapping. The process may include analyzing the query structure, identifying schema differences, and applying transformation rules to adapt the query syntax, data types, or table relationships to match the target database schema. The invention enables efficient data migration, system upgrades, and interoperability between heterogeneous database environments while maintaining query functionality and data integrity.
Unknown
November 26, 2019
Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.